Devices and Vaccines

Findings from the 2025 AMCP Foundation Symposium: Health Optimization 2.0.

The 2025 AMCP Foundation Symposium: Health Optimization 2.0 convened a select group of just over 70 managed care stakeholders in Dallas, Texas, on December 2-3, 2025. Via presentations and panel sessions, participants examined how precision medicine, data analytics, evolving policy, and health system design can address inequities in care delivery. Focus areas included precision medicine in oncolog...

Machine Learning-based Prediction of Unplanned Acute Care in Outpatients Receiving S-1 Chemotherapy.

BACKGROUND/AIM: The increasing use of oral anticancer agents in outpatient settings has led to a growing need for unplanned acute care (UAC) due to treatment-related adverse events. Early identification of high-risk patients is therefore clinically important. This study aimed to develop a machine learning-based model to predict UAC in outpatients receiving S-1 chemotherapy and to compare its perfo...

Deep learning enables rabies virus detection and antibody quantification in cell culture.

Rabies remains a major neglected disease, causing tens of thousands of deaths annually in endemic regions. Cell culture-based assays are central to ra...

Multimatrix QuantAI-LFIA: An On-Device Deep-Learning Biosensing Platform with Charge-Transfer-Active Labels for Intelligent Quantitative Analysis.

Commercial gold nanoparticle-based lateral flow immunoassays (LFIAs) are widely used for point-of-care (POCT) diagnostics; however, inefficient signal...

Generative Artificial Intelligence and 3D Printing in Craniomaxillofacial Deformities: A Narrative Review of Emerging Synergies.

Craniomaxillofacial deformities are primarily caused by congenital anomalies, trauma, or postoperative defects following tumor resection, involving bo...

Breath-Based Detection of Oral Diseases Using Sensors and Machine Learning.

OBJECTIVES: Diagnostic limitations contribute to variability in clinical decision-making, highlighting the need for objective diagnostic tools. Biomar...

Deep learning models based on post-procedural angiography for predicting the future risk of in-stent restenosis.

In-stent restenosis (ISR) remains a significant complication after percutaneous coronary intervention. Identifying patients at high risk for ISR from ...

Japanese regulation and approval process for medical artificial intelligence (AI) as software as a medical device (SaMD): Current status and emerging challenges.

The rapid expansion of artificial intelligence (AI) in healthcare has led to increasing adoption of AI-based software as a medical device (SaMD). This...

Clinical artificial intelligence (AI) in Japan: Regulatory pathways, domain-specific evidence, and its data infrastructure from an international perspective.

Artificial intelligence (AI) has advanced rapidly across clinical domains, generating both a growing evidence base and dedicated regulatory frameworks...

A novel deep learning-based grading system for assessing breast arterial calcification on mammograms, as an independent risk factor for predicting adverse cardiovascular events.

PURPOSE: To develop a deep learning-based framework for automated detection and grading of breast arterial calcification (BAC) on mammograms, and to e...

Automated CT Quantification of Iliofemoral Venous Arc Length Demonstrates Left-Sided Predominance and Sex-Specific Variation.

OBJECTIVE: In treatment planning for iliac venous obstruction, iliofemoral venous anatomy is central to procedural planning, but population-level refe...

CIST: A clade-informed sequence transformer framework for predicting influenza virus antigenicity.

Rapid antigenic evolution of influenza viruses complicates timely vaccine strain selection and renders prospective interpretation of serological assay...

Ultrasound-based assessment of peri-implant mucosal thickness: an ex vivo comparative study with artificial intelligence-assisted image analysis.

BACKGROUND: Mucosal thickness (MT) is a key factor influencing peri-implant soft-tissue response and outcomes in dental implantology. This ex vivo stu...

Augmenting Pediatric Care With Artificial Intelligence: Opportunities and Responsibilities for Nurse Practitioners.

BACKGROUND: Artificial intelligence (AI) is emerging as a critical tool for nurse practitioners delivering pediatric and adolescent and young adult (A...

Automated Identification of Surgical Site Infections From Electronic Medical Records: Retrospective Observational Predictive Modeling Study.

BACKGROUND: Surgical site infections (SSIs) affect 160,000 to 300,000 patients annually, increasing postoperative mortality, causing significant compl...

Neural networks and behavioral frameworks to analyse the impact of media and individual awareness for controlling epidemics.

Enhancing individual awareness and immunization are generally recognized as fundamental strategies for controlling infectious diseases. Awareness is i...

SFA-IoT: segment-to-flow aligned adversarial defense for interpretable IoT device identification.

Existing ML-based IoT device identification models achieve strong performance on clean data but degrade substantially when even small adversarial pert...

Rational design of an optimized ferritin nanoparticle vaccine targeting both SARS-CoV-2 and MERS-CoV.

BACKGROUND: Coronaviruses including SARS-CoV-2 and MERS-CoV remain threats to global health. Ferritin nanoparticle-based vaccines are promising platfo...

Detection of non-invasive sexing of early chick embryos in intact eggs using laser speckle contrast imaging and deep neural networks.

The ability to image blood flow in early-stage avian embryos has significant applications in developmental biology, drug and vaccine testing, as well ...

Deep Learning Based on Swin-Transformer and 3D U-Net: Implant Three-Dimensional Position Planning.

INTRODUCTION AND AIMS: This study aimed to devise a deep learning-based model for the automated identification of anatomical mandibular lingual concav...